This study presents a model-based analysis of the groundconnectivity performance of the future Santa Lucia-Mexico City multi-airport system. The plan of the currentgovernment is to connect the two airports by a dedicatedline, either by bus or other transport so that passengersand airlines can get the benefit of a coordinatedoperation. Performance indicators such as minimumconnecting time, vehicle utilization and passengerwaiting time are used to evaluate the future performance.Results reveal that when all passengers are allowed to usethe connection, a big number of vehicles are required forproviding a good level of service while in the case of arestricted use to only transfer passengers the operationwith Bus would have a good performance.
It is expected that future transportation technologies will positively impact how passengers travel to their destinations. Europe aims to integrate air transport into the overall multimodal transport network to provide better service to passengers, while reducing travel time and making the network more resilient to disruptions. This study presents an approach that investigates these aspects by developing a simulation platform consisting of different models, allowing us to simulate the complete door-to-door trajectory of passengers. To address the future potential, we devised scenarios considering three time horizons: 2025, 2035, and 2050. The experimental design allowed us to identify potential obstacles for future travel, the impact on the system’s resilience, and how the integration of novel technology affects proxy indicators of the level of service, such as travel time or speed. In this paper, we present for the first time an innovative methodology that enables the modelling and simulation of door-to-door travel to investigate the future performance of the transport network. We apply this methodology to the case of a travel trajectory from Germany to Amsterdam considering a regional and a hub airport; it was built considering current information and informed assumptions for future horizons. Results indicate that, with the new technology, the system becomes more resilient and generally performs better, as the mean speed and travel time are improved. Furthermore, they also indicate that the performance could be further improved considering other elements such as algorithmic governance.
MULTIFILE
This study examines the effect of seat assignment strategies on the transfer time of connecting passengers at a hub airport. Passenger seat allocation significantly influences disembarkation times, which can increase the risk of missed connections, particularly in tight transfer situations. We propose a novel seat assignment strategy that allocates seats to nonpaying passengers after check-in, prioritising those with tight connections. This approach diverges from traditional methods focused on airline turnaround efficiency, instead optimizing for passenger transfer times and reducing missed connections. Our simulation, based on real-world data from Paris-Charles de Gaulle airport, demonstrates that this passenger-centric model decreases missed connections by 12%, enhances service levels, reduces airline compensation costs, and improves airport operations. The model accounts for variables such as seat occupancy,luggage, and passenger type (e.g., business, leisure) and is tested under various scenarios, including air traffic delays.
MULTIFILE
